Papers by Polina Rozenshtein

2 papers
ESTeR: Combining Word Co-occurrences and Word Associations for Unsupervised Emotion Detection (2020.findings-emnlp)

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Challenge: Recent studies list as many as 154 human emotions, but most researchers agree on basic emotions such as anger, fear, disgust, sadness, surprise, and happiness.
Approach: They propose an unsupervised model for identifying emotions using a novel similarity function based on random walks on graphs.
Outcome: The proposed model can be computed efficiently and avoids dependence on labeled datasets.
I Wish I Would Have Loved This One, But I Didn’t – A Multilingual Dataset for Counterfactual Detection in Product Review (2021.emnlp-main)

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Challenge: Using machine translation, counterfactual statements are often found in natural languages.
Approach: They annotate a multilingual CFD dataset from Amazon product reviews covering counterfactuals written in English, German, and Japanese languages.
Outcome: The proposed dataset is robust against selection biases due to cue phrase-based sentence selection.

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